qual_fun: calculate model performance metrics
In aemon-j/LakeEnsemblR: Run Ensemble of Lake Models
View source: R/helper_calibration.R
qual_fun R Documentation
calculate model performance metrics
Description
function that calculates different estimations for model accuracy, namely: root mean squared
error (rmse), (Nash-Sutcliff) model efficiency (nse), Pearson corelation coefficient (r),
relative error (re), mean absolute error (mae), and normalized mean absolute error (nmae).
returns a data.frame containing the six quality estimates
Usage
qual_fun(O, P)
Arguments
O
data.frame containing observed values, first row is datetime
P:
data.frame containing predicted values, first row is datetime
aemon-j/LakeEnsemblR documentation built on April 11, 2025, 10:09 p.m.
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View source: R/helper_calibration.R
| qual_fun | R Documentation |
calculate model performance metrics
Description
function that calculates different estimations for model accuracy, namely: root mean squared error (rmse), (Nash-Sutcliff) model efficiency (nse), Pearson corelation coefficient (r), relative error (re), mean absolute error (mae), and normalized mean absolute error (nmae). returns a data.frame containing the six quality estimates
Usage
qual_fun(O, P)
Arguments
O |
data.frame containing observed values, first row is datetime |
P: |
data.frame containing predicted values, first row is datetime |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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